Integrating geospatial, hydrogeological, and geophysical data to identify groundwater recharge potential zones in the Sulaymaniyah basin, NE of Iraq by Sarkhel H. Mohammed, Musaab A. A. Mohammed, Hawber Ata Karim, Diary A. Mohammed AL-Manmi, Bakhtiar Qader Aziz, Asaad I. Mustafa, Péter Szűcs

“…The results identified three potential zones for groundwater recharge: low (11.26%), moderate (45.51%), and high (43.23%). Validation using ERT data and receiver operating characteristics (ROC) analysis revealed strong agreement, with an area under the curve (AUC) accuracy of 86%. …”
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Leveraging Social Media Data to Understand COVID-19 Prevention Measures in Construction: A Machine Learning Approach by Emmanuel B. Boateng, Daniel Oteng, Dan N. O. Bonsu, Vinod Gopaldasani

“…In addition, sentiment analysis demonstrated interesting polarisation around the topic areas. …”
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EPIDEMICAL IMPORTANCE OF LUNG TUBERCULOMA, THE EFFICIENCY OF THEIR SURGICAL AND NON- SURGICAL TREATMENT BASED ON DATA FROM THE REPUBLIC OF TATARSTAN by R. Sh. Valiev, N. R. Valiev, I. Ya. Iksanov, M. S. Filatova

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Early prediction of colorectal adenoma risk: leveraging large-language model for clinical electronic medical record data by Xiaoyu Yang, Jinjian Xu, Hong Ji, Jun Li, Bingqing Yang, Liye Wang

“…ObjectiveTo develop a non-invasive, radiation-free model for early colorectal adenoma prediction using clinical electronic medical record (EMR) data, addressing limitations in current diagnostic approaches for large-scale screening.DesignRetrospective analysis utilized 92,681 cases with EMR, spanning from 2012 to 2022, as the training cohort. …”
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Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data by Yuan Tao, Guo Hua, Sun Min, Lu Xiao-hong, Jiang Jia-hui, Tang Biao, He Cai-feng, Zhang Cheng, Ci Chao, Wu Jian-ping

“…Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE.Results In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. …”
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Effect of natural and synthetic noise data augmentation on physical action classification by brain–computer interface and deep learning by Yuri Gordienko, Nikita Gordienko, Vladyslav Taran, Anis Rojbi, Sergii Telenyk, Sergii Telenyk, Sergii Stirenko

“…The main aim of this study was to imitate and investigate environmental influence by the proposed noise data augmentation (NDA) of two kinds: (i) natural NDA by inclusion of noise EEG data from neighboring regions by increasing the sampling size N and the different offset values for sample labeling and (ii) synthetic NDA by adding the generated Gaussian noise. …”
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THE EXPERIENCE OF THE AUTOMATION OF THE STATISTICAL REPORTING FORMATION ON WAGES IN MULTIDISCIPLINARY MEDICAL INSTITUTION by O. E. Karpov, D. N. Nikitenko, O. Ya. Gembara, T. A. Manakova

“…Thus, the introduction of multidimensional analytical reporting made it possible to facilitate the labor-intensive process of making strategic management decisions by the administration of the institution.The authors concluded that the availability of such a tool in the healthcare system could help accelerating the operational processing of information for data analysis, as well as the generation of reports in various sections with an established depth of detail.…”
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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…Pearson correlation analysis was used for sensitivity analysis. The results showed that in all models, temperature, solubility, and pressure have a negative correlation with pH, while salinity has a positive correlation. …”
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Construction and validation of a predictive model for the risk of osteoporosis in patients with chronic kidney disease based on NHANES data. by Chunjie She, Hefeng Liu

“…The performance of the prediction model was assessed using various metrics, including the area under the receiver operating characteristic curve (AUC), calibration curve, the Hosmer-Lemeshow test, and decision curve analysis (DCA).…”
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A hybrid deep learning framework for short-term load forecasting with improved data cleansing and preprocessing techniques by Muhammad Sajid Iqbal, Muhammad Adnan, Salah Eldeen Gasim Mohamed, Muhammad Tariq

“…The process unfolds with data collection, followed by rigorous standardization, preprocessing, and cleansing of demand and generation data. …”
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A Hybrid Data-Driven Method for Main Circuit Gound Faults Diagnosis in Electrical Traction Drive Systems by Xinyao Hou, Juntong Liu, Jinxin Zhang, Qiang Ni

“…To improve the efficiency of train operation and ensure driving safety, this paper proposes a hybrid data-driven MCGF diagnosis method. …”
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Development of a clinical nomogram for predicting sarcopenia in patients with chronic obstructive pulmonary disease based on NHANES data by Xingfu Fan, Jin Zhao, Yang Luo, Xiaofang Li, Wenqin Tan, Shiping Liu

“…Calibration curve, decision curve analysis (DCA), and area under receiver operating characteristic curve (AUC) were applied in testing performance in prediction model.ResultsThe nomogram was constructed based on four predictive factors: gender, height, BMI, and WWI. …”
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Evaluating Transit-Oriented Development Performance: An Integrated Approach Using Multisource Big Data and Interpretable Machine Learning by Huadong Chen, Kai Zhao, Zhan Zhang, Haodong Zhang, Linjun Lu

“…This study suggests a multi-indicator TOD performance evaluation method based on a multi-indicator approach grounded in the analysis of multisource urban big data, revealing the role of rail transit TOD station characteristics on critical indicators of station operation through an interpretable machine learning approach. …”
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Leveraging multi-source data and teleconnection indices for enhanced runoff prediction using coupled deep learning models by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

“…Stepwise Regression Analysis (SRA) was employed to effectively handle high-dimensional data and multicollinearity, ensuring that only the most influential predictive variables were retained. …”
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Nature, sector, and GVC participation of firms: empirical insights from firm-level data in selected SSA countries by Alhassan Abdul-Wakeel Karakara, Camara Kwasi Obeng, Mark Kojo Armah, Jacob Nunoo

“…Firms should be encouraged to become shareholding or partnership firms to boost their GVC chances.Impact statement This paper analysis the GVC participation of firms in sub-Saharan Africa by arguing that the Nature of firm, the Sector of operation and other firm characteristics greatly drives firm GVC participation in SSA. …”
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Development of a High-Reliability Hybrid Data Transmission System for Unmanned Surface Vehicles Under Interference Conditions by Sergiy Kurdiuk, Vadym Dremliuk, Oleksiy Melnyk, Oleg Onishchenko, Oleksij Fomin, Václav Píštěk, Pavel Kučera

“…This paper discusses modern approaches to the creation of a highly reliable data transmission system for unmanned surface vehicles (USVs) operating under interference conditions. …”
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A Robust U-Net-Based Approach for Accurate Brain Tumor Segmentation Using Multimodal MRI Data by Mohammad Talal Ghazal

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Mobile Payment and Delivery Services in Vietnam During the Covid-19 Pandemic: A Data Mining Analytics Investigation by Shu-Hsien Liao, Retno Widowati, Pham Nguyen My Hanh

“…This empirical study investigates Vietnamese consumer behaviors with mobile payment and delivery services during the pandemic. Data mining analytics, including association rules and clustering analysis for investigating mobile payment and delivery service business model development. …”
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A Hybrid Approach to Credit Risk Assessment Using Bill Payment Habits Data and Explainable Artificial Intelligence by Cem Bulut, Emel Arslan

“…Therefore, the dataset was prepared for the analysis by using data cleaning, feature selection, and sampling techniques. …”
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Elucidating Parasitic Currents in Proton‐Exchange‐Membrane Electrolytic Cells via Physics‐Based and Data‐Driven Modeling by Violeta Karyofylli, K. Ashoke Raman, Linus Hammacher, Yannik Danner, Hans Kungl, André Karl, Eva Jodat, Rüdiger‐A. Eichel

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